In this study, a novel electric load forecaster based on adaptive Fuzzy Neural Networks (FNN) and
using Genetic Algorithm (GA) mixed with Gradient Descent (GD) is proposed to make it to posses the human
learning ability. The proposed SDSA-FNN is firstly compared with various methods applied on function
approximations. Moreover, it is applied on electric load forecasting application and verified on electric load
data recorded on Macao power system. The simulation results reveal that the proposed methodology not only
keeps the traditional objective function.